No abstract

GRAS genes are suggested to be grouped into plant-specific transcriptional regulatory families that have been reported to participate in multiple processes, including plant development, phytohormone signaling, the formation of symbiotic relationships, and response to environmental signals. GRAS genes have been characterized in a number of plant species, but little is known about this gene family in Citrus sinensis. In this study, we identified a total of 50 GRAS genes and characterized the gene structures, conserved motifs, genome localizations and cis-elements within their promoter regions. According to their structural and phylogenetic features, the identified sweet orange GRAS members were divided into 11 subgroups, of which subfamily CsGRAS34 was sweet orange-specific. Based on publicly available RNA-seq data generated from callus, flower, leaf and fruit in sweet orange, we found that some sweet orange GRAS genes exhibited tissue-specific expression patterning. Three of the six members of subfamily AtSHR, particularly CsGRAS9, and two of the six members of subfamily AtPAT1 were preferentially expressed in leaf. Moreover, protein-protein interactions with CsGRAS were predicted. Gene expression analysis was performed under conditions of phosphate deficiency, and GA3 and NaCl treatment to identify the potential functions of GRAS members in regulating stress and hormone responses. This study provides the first comprehensive understanding of the GRAS gene family in the sweet orange genome. As such, the study generates valuable information for further gene function analysis and identifying candidate genes to improve abiotic stress tolerance in citrus plants.

Certain progress has been made in fault diagnosis under cross-domain scenarios recently. Most researchers have paid almost all their attention to promoting domain adaptation in a common space. However, several challenges that will cause negative transfer have been ignored. In this paper, a reweighting method is proposed to overcome this difficulty from two aspects. First, extracted features differ greatly from one another in promoting positive transfer, and measuring the difference is important. Measured by conditional entropy, the weight of adversarial losses for those well aligned features are reduced. Second, the balance between domain adaptation and class discrimination greatly influences the transferring task. Here, a dynamic weight strategy is adopted to compute the balance factor. Consideration is made from the perspective of maximum mean discrepancy and multiclass linear discriminant analysis. The first item is supposed to measure the degree of the domain adaptation between source and the target domain, and the second is supposed to show the classification performance of the classifier on the learned features in the current training epoch. Finally, extensive experiments on several bearing fault diagnosis datasets are conducted. The performance shows that our model has an obvious advantage compared with other common transferring algorithms.

Background. Benzoylmesaconine (BMA), the most abundant monoester alkaloid in Aconitum plants, has some biological activities and is a potential therapeutic agent for inflammation-related diseases. However, the potential anti-inflammatory mechanisms of BMA have not been clarified. Purpose. This study aimed to investigate the underlying molecular mechanisms of the anti-inflammatory action of this compound using lipopolysaccharide (LPS)-activated RAW264.7 macrophages. Methods. The release of pro-inflammatory cytokines and mediators were detected by nitric oxide (NO) assays, reactive oxygen species (ROS) assays, and enzyme-linked immunosorbent assays (ELISA) in LPS-activated RAW264.7 macrophage cells. Quantitative real-time PCR was used to measure the gene expression of interleukin (IL)-1β, tumor necrosis factor (TNF)-α, IL-6, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2). Cell viability was determined using a cell counting kit-8 (CCK-8) assay. The expression of iNOS, COX-2, mitogen-activated protein kinase (MAPK), and nuclear factor-κB (NF-κB)-related proteins were detected by western blot, and nuclear translocation of p65 was observed by immunofluorescence. Results. BMA significantly decreased the production of IL-1β, IL-6, TNF-α, PGE2, NO, and ROS and inhibited the protein and mRNA levels of COX-2 and iNOS in LPS-activated RAW264.7 macrophages. Moreover, LPS-induced phosphorylation of IκBα, JNK, p38, and ERK; degradation of IκBα; and nuclear translocation of p65 were significantly suppressed by BMA treatment. Conclusion. These findings demonstrate that the anti-inflammatory effect of BMA was through the suppression of the NF-κB and MAPK signaling pathways and that it may be a therapeutic agent targeting specific signal transduction events required for inflammation-related diseases.

Background: The availability of 12 fully sequenced Drosophila species genomes provides an excellent opportunity to explore the evolutionary mechanism, structure and function of gene families in Drosophila. Currently, several important resources, such as FlyBase, FlyMine and DroSpeGe, have been devoted to integrating genetic, genomic, and functional data of Drosophila into a well-organized form. However, all of these resources are gene-centric and lack the information of the gene families in Drosophila.